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Mastering Apache Spark 2.x

You're reading from   Mastering Apache Spark 2.x Advanced techniques in complex Big Data processing, streaming analytics and machine learning

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781786462749
Length 354 pages
Edition 2nd Edition
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Author (1):
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Romeo Kienzler Romeo Kienzler
Author Profile Icon Romeo Kienzler
Romeo Kienzler
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Table of Contents (15) Chapters Close

Preface 1. A First Taste and What’s New in Apache Spark V2 2. Apache Spark SQL FREE CHAPTER 3. The Catalyst Optimizer 4. Project Tungsten 5. Apache Spark Streaming 6. Structured Streaming 7. Apache Spark MLlib 8. Apache SparkML 9. Apache SystemML 10. Deep Learning on Apache Spark with DeepLearning4j and H2O 11. Apache Spark GraphX 12. Apache Spark GraphFrames 13. Apache Spark with Jupyter Notebooks on IBM DataScience Experience 14. Apache Spark on Kubernetes

Summary

Apache Spark in the cloud is the perfect solution for data scientists and data engineers who want to concentrate on getting the actual work done without being concerned about the operation of an Apache Spark cluster.

We saw that Apache Spark in the cloud is much more than just installing Apache Spark on a couple of virtual machines. It comes as a whole package for the data scientist, completely based on open-source components, which makes it easy to migrate to other cloud providers or to local datacenters if necessary.

We also learned that, in a typical data science project, the variety of skills is huge, which is taken care of by supporting all common programming languages and open-source data analytics frameworks on top of Apache Spark and Jupyter notebooks, and by completely eliminating the necessity for operational skills required to maintain the Apache Spark cluster...

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